Speaker 1: We're from Mahart. We're Innovation, Money and Power Collie in
Speaker 1: Silicon Vallet NBN. This is Bloomberg Technology with Caroline Hyde and.
Speaker 2: Ed Ludlow.
Speaker 3: Live from San Francisco to our TV and radio audiences
Speaker 3: around the world. Welcome to a special edition of Bloomberg Technology.
Speaker 3: I'm Ed Ludlow. In just a few moments in vidio,
Speaker 3: CEO Jensen Wang will join us for a live interview
Speaker 3: following their latest earnings report, the company posting a revenue
Speaker 3: forecast that beat consensus that fell short to some of
Speaker 3: the most optimistic estimates, stoking concern that the explosive growth
Speaker 3: is waning. Let's get right to Bloomberg Semiconductor correspondent Ian King,
Speaker 3: who joins me on set. Let's start with the basics,
Speaker 3: the fiscal third quarter forecast and we learned through it.
Speaker 4: Yeah, that forecast was fine. If you compare it to consensus,
Speaker 4: it was there or thereabouts. And for most of the
Speaker 4: companies in the world, that would be great and everybody
Speaker 4: would be happy. But this is in video. This is
Speaker 4: a company which you know, beats pretty much every quarter
Speaker 4: and by an order of magnitude, and it didn't do that,
Speaker 4: and it didn't indicate it would do that, and that
Speaker 4: raised a lot of questions. As we heard on the.
Speaker 3: Call, there are many storylines. I think the demand from
Speaker 3: the hyperscalers is clearly intact, but Blackwell was everything. I
Speaker 3: want to play a SoundBite of what Jensen Wong said
Speaker 3: about Blackwell. Listened to this.
Speaker 2: The change to the mask is complete. There were no
Speaker 2: functional changes necessary, and so we're sampling functional samples of
Speaker 2: Blackwell Grace Blackwell in a variety of system configurations as
Speaker 2: we speak.
Speaker 3: The main point here is that there was not a
Speaker 3: design issue with Blackwell itself as had been reported, but
Speaker 3: based on what Nvidia said, this was about the production mechanism.
Speaker 3: Blue Bazine King, you did a very good job in
Speaker 3: the top Life blog of explaining a GPU mask. Could
Speaker 3: you just try to give a short version of that
Speaker 3: to our audience.
Speaker 4: Yeah, the mask is basically the blueprint, which basically that
Speaker 4: is used to burn in the circuit onto the surface
Speaker 4: of the chip to give it its function, right, and
Speaker 4: it is a very important step. That's the fundamental blueprint.
Speaker 4: And they were saying we didn't get it wrong, but
Speaker 4: when it came to manufacturing, it didn't produce as many
Speaker 4: good chips as we wanted, so we made some tweaks
Speaker 4: to that. Didn't have to redesign it, but made some tweaks,
Speaker 4: and that is helping us to get a better yield.
Speaker 3: It's worth noting at this stage the stocks down almost
Speaker 3: seven percent in after hours, have been down more at
Speaker 3: the conclusion of the call. I think basically because we
Speaker 3: didn't learn enough about Blackwell. What they said was in
Speaker 3: the fiscal fourth quarter of fiscal year twenty five, there
Speaker 3: will be several billion dollars of sales through Blackwell. Why
Speaker 3: does the market want more and what does it want?
Speaker 4: They wanted a reassurance from in videos management, and they
Speaker 4: wanted reassurance in the form of details. They wanted gens
Speaker 4: to PuTTY's arm around everybody and say, don't worry, It'll
Speaker 4: be fine. This is how much I'm going to get.
Speaker 4: They asked consistently, We're asked questions of how many billions
Speaker 4: and when will those billions exactly come in and collect. Kretz,
Speaker 4: the CFO and Jensen Wang essentially avoided that question and
Speaker 4: refuse to give that precise reassurance.
Speaker 3: We're showing some of the after ours reaction, not just
Speaker 3: in in video itself, but some of its peers, both
Speaker 3: on the chip making side the server equipment providers, and
Speaker 3: I think AMD and ARM in particular are very noteworthy.
Speaker 3: Bloombogty and King stay with us. I want to go
Speaker 3: out to Chicago and Bloomberg's Ryan for Lostelka on I
Speaker 3: Equities team and Ryan. That's the broad summary from me
Speaker 3: about the names moving and after hours there's probably a
Speaker 3: bigger picture after ours movement in the markets as well,
Speaker 3: start with in video and work outward from there.
Speaker 5: Sure, well, one thing I would say about in videos
Speaker 5: after hours decline is that it does come after a
Speaker 5: very strong year to day performance. I think it closed
Speaker 5: up more than one hundred and fifty percent this year,
Speaker 5: So even though the re forecast was maybe a little
Speaker 5: bit shy of some of the most optimistic expectations, it
Speaker 5: did beat expectations. And it is, you know, coming off
Speaker 5: such a huge gain. So it's not necessarily surprising to
Speaker 5: see a little bit of a consolidation now. And I
Speaker 5: think even the declient is a little bit less and
Speaker 5: the options market was anticipating. So just some context there
Speaker 5: for looking at the declient. But you're right that pretty
Speaker 5: much we are seeing widespread weakness following this report, all
Speaker 5: the megacaps are, you know, modestly lower. We are seeing
Speaker 5: much more pronounced weakness in other chip makers and chip
Speaker 5: design companies and so forth. So yeah, certainly it does
Speaker 5: seem like the initial read through here is negative, but
Speaker 5: again it does come after a very strong start to
Speaker 5: the year.
Speaker 3: We made a big deal about this earnings print for
Speaker 3: quite a long time. I look at something like an
Speaker 3: investco QQQ, the ETF that tracks the nast that one hundred,
Speaker 3: and I think it's down around a percentage point, right,
Speaker 3: But in true in the market's reaction, was this the
Speaker 3: macro level event that we thought it was going to be.
Speaker 5: That's a great question. I would say that it's kind
Speaker 5: of close enough in line with expectations, even if it
Speaker 5: is a little bit shy the most optimistic ones that
Speaker 5: I don't think this is going to really cause people
Speaker 5: to really change how they're allocating, change their opinions on
Speaker 5: AI's as kind of fundamental secular driver. But maybe in
Speaker 5: the near term we do see a little bit of weakness.
Speaker 5: I mean, again, some of these stocks have been moving
Speaker 5: up so much there have been sort of kind of
Speaker 5: growing calls about their valuation. Some concerns about that. I
Speaker 5: don't know if this is the kind of absolute blowout
Speaker 5: that will just you know, cause people to continue piling
Speaker 5: into the the way that they were doing earlier this year.
Speaker 3: There is a lot in the news cycle inclusive of
Speaker 3: and outside of video. I think one of the names
Speaker 3: that you note in after ours is super Micro. It's
Speaker 3: down significantly. There's an video relationship to that, and then
Speaker 3: there's the news around that name in and of itself.
Speaker 5: Yeah. Absolutely so. We saw yesterday a short report came
Speaker 5: out Today's delaying the filing of the tin K. You know,
Speaker 5: both of those cars does a weakness in the stock.
Speaker 5: I think today it was down more than double digits,
Speaker 5: So you know, a lot of reasons to be concerned
Speaker 5: there in general. And it is one of Nvidia's biggest customers.
Speaker 5: I think it's the third largest, So you know, this
Speaker 5: is just another reason for people who might have been
Speaker 5: kind of souring on super Micro to you know, maybe
Speaker 5: be pulling the cell button.
Speaker 2: A little bit.
Speaker 3: Bloomdo's Ryan for Selica with the after hours action out
Speaker 3: of Chicago. Thank you. Let's get the reaction from the
Speaker 3: cell side with one of the stocks, relative bears d
Speaker 3: A Davidson's Gil Luria had a neutral rating and a
Speaker 3: street low ninety dollars price target on shares of Nvidia.
Speaker 3: He joins US now and Gil, I guess does that
Speaker 3: change your barished perspective on the stock and your main
Speaker 3: takeaway from the analyst school, the quarter was.
Speaker 1: A very good quarter there. Ability to continue to grow
Speaker 1: delivering chips at this rate at this scale is fantastic
Speaker 1: and unprecedented. I don't think there's much of a revenue
Speaker 1: issue here, of a growth issue here. I think a
Speaker 1: little bit of a pushback is probably more around the
Speaker 1: margin situation. You had a good conversation with Ian about
Speaker 1: Blackwell and some of the moving pieces part of what's
Speaker 1: happening with Blackwell. It's a new product, it's got a
Speaker 1: few hitches along the way that put pressure on gross margins,
Speaker 1: and then operating margins grew more than anticipated, so less
Speaker 1: of the top line upside flowed to the bottom line.
Speaker 1: And that's probably where investors are getting a little bit
Speaker 1: more cautious than they were before, because in the last
Speaker 1: several quarters, the huge upside to revenue flowed all the
Speaker 1: way to the bottom line, creating huge upside there to
Speaker 1: believe in and Nvidia right now is to believe twenty
Speaker 1: twenty six calendar is going to be about two hundred
Speaker 1: billion of revenue and about four and a half to
Speaker 1: five dollars of earnings. That's only possible if they continue
Speaker 1: to get this type of growth on the top line
Speaker 1: and more leverage. And the second part of that equation
Speaker 1: looks a little less certain right now.
Speaker 3: Gil. When you said that two hundred billion dollar figure,
Speaker 3: Bloombergsy and King, who's covered semi conductors at this company
Speaker 3: since nineteen ninety eight, sat next to me still, for
Speaker 3: what it's worth, gave a little smile. I mean, it's
Speaker 3: an astonishing figure. I think there's a lot of emphasis
Speaker 3: here on Blackwell. How did you react to the news
Speaker 3: of several billion dollars in fiscal fourth with Blackwell and
Speaker 3: the explanation that this was a production issue impacting the ramp,
Speaker 3: not a sort of core design issue around the product itself.
Speaker 1: So, first of all, our estimate is far less than
Speaker 1: two hundred billion for twenty twenty six.
Speaker 3: But that's you're a relative bear, Gill and I got
Speaker 3: that bit right.
Speaker 1: I think in terms of Blackwell, what happened to in
Speaker 1: n videos they used to be on a two year
Speaker 1: cycle for the data center product, and they decided to
Speaker 1: aggressively move to a one year cycle and then put
Speaker 1: a lot of new feature functionality and bundle into the
Speaker 1: Blackwell platform. So that was a very aggressive agenda, and
Speaker 1: it's not that surprising that there's some challenges that they
Speaker 1: have to encounter. If they can still ship in their
Speaker 1: fiscal fourth quarter, that's a very good sign. And by
Speaker 1: the way, their customers don't really care that much. Their
Speaker 1: customers are just going to continue to buy the latest
Speaker 1: and greatest, and if that's the Age two hundred, they'll
Speaker 1: just continue to buy h two hundred. They have made
Speaker 1: that abundantly clear on their conference calls, Microsoft, Meta, Amazon, Google, Tesla.
Speaker 1: Elon Musk made it abundantly clear they'll buy as much
Speaker 1: GPUs as and Video can produce, at least this year,
Speaker 1: because they're saying the demand signals are there. As long
Speaker 1: as the demand signals are there, they'll buy whatever and
Speaker 1: Video is selling, and towards the end of the year,
Speaker 1: a piece of that will be Blackwell.
Speaker 3: Gil Jensen Wong was it pains and gave a detailed
Speaker 3: answer that basically summarizing video as a systems vendor the
Speaker 3: discussion around Envy link, CPUs, everything beyond GPU. How much
Speaker 3: credit do you assign the company for that, the sort
Speaker 3: of complete systems that they sell.
Speaker 1: A tremendous amount of credit. Let's start with the beginning.
Speaker 1: When history is written, we'll talk about how Jensen Wangen
Speaker 1: Nvidia created the capabilities that make generative AI possible today
Speaker 1: in a similar way that Elon Musk is responsible for
Speaker 1: the electric vehicle. And part of the genius wasn't just
Speaker 1: seeing that this is coming, that accelerate computers coming, AI
Speaker 1: capabilities is coming well before anybody else did. It's also
Speaker 1: realizing that in order to create a moat around the chip,
Speaker 1: they need to do a couple of things. One is
Speaker 1: to own the proprietary software around that KUDA, but the
Speaker 1: other thing is to enhance the bundle as much as possible.
Speaker 1: These GPUs work in a raise when they work together,
Speaker 1: ten thousands or sometimes tens of thousands of GPUs together.
Speaker 1: When you box those up in a box with multiple GPUs, CPUs, wiring,
Speaker 1: cabling and firmware, you make it harder for your competitors
Speaker 1: to catch. And they've done a remarkable job of that.
Speaker 3: I also wonder about all the rest The story thus
Speaker 3: far has been about the hyperscale is a meta five names,
Speaker 3: essentially being the core customer of Nvidia. We got some
Speaker 3: detail on low double digit billions sales this year in
Speaker 3: sovereign AI. Do you see evidence that the market is
Speaker 3: broadening out beyond just the cloud providers?
Speaker 1: Not really. It seems like those five are still a
Speaker 1: substantial amount of the revenue. And those five have in
Speaker 1: their most recent calls said some interesting things. One of
Speaker 1: them is that they consistently said they are over investing.
Speaker 1: So they said they definitely want to invest more. We're
Speaker 1: seeing that in results today. But they also use the
Speaker 1: term over investing. Over investing is something you do before
Speaker 1: you do the other thing, and they made it clear
Speaker 1: that they're only going to do so when they have
Speaker 1: the demand signals. If for whatever reason, demand for AI
Speaker 1: capacity goes down, for instance, because compute doesn't continue to
Speaker 1: drive performance of foundational models, you're going to see those
Speaker 1: same five actors pull back and say, you know, maybe
Speaker 1: we have enough data center capacity, or maybe what we
Speaker 1: have in the pipeline is enough. And that's the concern
Speaker 1: for twenty twenty five and twenty six is that those
Speaker 1: very companies could do that. Beyond that, these are the
Speaker 1: same companies that are developing their own chips. They're at
Speaker 1: various stages of this, but Google's TPUs are probably as
Speaker 1: good as in videos, so in terms of their internal
Speaker 1: use and selling to customers such as Apple, Google's already
Speaker 1: caught up, Amazon's catching up, Meta and Microsoft are earlier stages.
Speaker 1: But these same companies that are buying every GPU from
Speaker 1: video they can gil will be the ones that will
Speaker 1: buy possibly less next year in the year after that.
Speaker 3: I just want to reflect for our TV and radio audience,
Speaker 3: there are people tuned in around the world. My understanding
Speaker 3: is there are watch parties in cities from New York
Speaker 3: to London. For this earnings. We've hyped it up for weeks.
Speaker 3: Probably this is the most unique earnings print that I've
Speaker 3: covered in my career. What about for you in the
Speaker 3: semiconductor space, Why is this so different?
Speaker 1: Well, so, first of all, I tried to participate by
Speaker 1: wearing a video green today. But importantly and video is
Speaker 1: important because of how much they've added to the cumulative
Speaker 1: earnings of this in P. Five hundred and the cumulative performance.
Speaker 1: But I wouldn't necessarily extrapolate their success or sometimes setbacks
Speaker 1: to the rest of the market because what they do
Speaker 1: is very specific. The growth and data center construction and
Speaker 1: data center a GPU fulfillment into those data centers is
Speaker 1: a very small set of companies. I'd argue, and Video
Speaker 1: is sucking the oxygen for the room from a lot
Speaker 1: of other technology companies. So we celebrate within Video because
Speaker 1: they've added so much value I wouldn't necessarily read through
Speaker 1: to the rest of technology.
Speaker 3: Guillerya of DA Davidson, the relatively most bearish or perhaps
Speaker 3: the least bullish name on the street. Thank you so
Speaker 3: welcome to this special edition of Bloomberg Technology for our
Speaker 3: TV and radio audience around the world. Joining me now
Speaker 3: is Jensen One, CEO of Nvidia, straight from the analyst's call,
Speaker 3: and Jensen, good evening, good afternoon to you. I think
Speaker 3: the market wanted more on Blackwell, they wanted more specifics,
Speaker 3: and I'm trying to go through all of the call
Speaker 3: and the transcript. It seems like a very clearly this
Speaker 3: was a production issue and not a fundamental design issue
Speaker 3: with Blackwell, but the deployment in the real world, what
Speaker 3: does that look like tangibly and is there a sort
Speaker 3: of delay in the timeline of that deployment and thus
Speaker 3: revenue from that product.
Speaker 6: I let's see, that's just the fact that I was
Speaker 6: so clear and it wasn't clear enough kind of tripped
Speaker 6: me up there right away. And so let's see. We
Speaker 6: we made a mass change to improve the yield. Functionality
Speaker 6: of Blackwell is wonderful. We're sampling Blackwell all over the
Speaker 6: world today. We show people giving tours to people of
Speaker 6: the Blackwall systems that we have up and running. You
Speaker 6: could find pictures of Blackwall systems all over the web.
Speaker 6: We have started volume production. Volume production will ship in
Speaker 6: Q four. Q four, we will have billions of dollars
Speaker 6: of Blackwell revenues and we will ramp from there. We
Speaker 6: will ramp from there. The demand for Blackwell far exceeds
Speaker 6: its supply, of course in the beginning, because the demand
Speaker 6: is so great, But we're going to have lots and
Speaker 6: lots of supply and we will be able to ramp.
Speaker 6: Starting in Q four, we have billions of dollars of
Speaker 6: revenues and we will ramp from there into Q one
Speaker 6: into Q two and two next year. We're going to
Speaker 6: have a great next year.
Speaker 3: Well, Jensen, what is the demand for accelerated computing beyond
Speaker 3: the hyperscalers and meta.
Speaker 6: Hyperscalers represent about forty five percent of our total data
Speaker 6: center business. We're relatively diversified today. We have hyperscalers, we
Speaker 6: have Internet service providers, we have sovereign AIS, we have
Speaker 6: industries enterprises, so it's fairly fairly diversified. A site outside
Speaker 6: of hyperscalers is the other fifty five percent. Now, the
Speaker 6: application use across all of that, all of that data
Speaker 6: center starts with accelerated computing. Accelerated computing does everything, of course,
Speaker 6: from well the models the things that we know about,
Speaker 6: which is generative AI, and that gets most of the attention.
Speaker 6: But at the core we also do database processing, pre
Speaker 6: and post processing of data before you use it for
Speaker 6: generative AI, trans coding, scientific simulations, computer graphics of course,
Speaker 6: image processing of course. And so there's tons of applications
Speaker 6: that people use are accelerated computing for, and one of
Speaker 6: them is generative AI. And so let's see what else
Speaker 6: can I say? I think that's the.
Speaker 3: Lever jump in Jensen please on Sovereign AI. You and
Speaker 3: I've talked about that before, and it was so interesting
Speaker 3: to hear something behind it that in this fiscal year
Speaker 3: there will be low double digit I think you said
Speaker 3: billions of dollars in sovereign AI sales. But to the
Speaker 3: lay person, what does that mean. It means deals with
Speaker 3: specific governments, if so, where.
Speaker 6: It's not necessarily Sometimes it deals with a particular regional
Speaker 6: service provider that's been funded by the government. And oftentimes
Speaker 6: that's the case in a case of in the case
Speaker 6: of Japan, for example, the the Japanese government came out
Speaker 6: and UH offered UH subsidies of a couple of billion dollars.
Speaker 6: I think for several different internet companies and telcos to
Speaker 6: be able to fund their AI infrastructure. UH India has
Speaker 6: a sovereign AI initiative going and they're building their AI infrastructure. Canada,
Speaker 6: the UK, France, Italy, missing somebody, Singapore, Malaysia, UH. You know,
Speaker 6: a large number of countries are subsidizing their regional data
Speaker 6: centers so that they could become able to build out
Speaker 6: their AI infrastructure. They recognize that their countries UH knowledge,
Speaker 6: their countries data digital data is also their natural resource,
Speaker 6: not just the land they're sitting on, not just the
Speaker 6: air above them. But they realize now that their digital
Speaker 6: knowledge is part of their natural and national resource, and
Speaker 6: they are to harvest that and process that and transform
Speaker 6: it into their national digital intelligence. And so this is
Speaker 6: what we call sovereign AI. You could imagine almost every
Speaker 6: single country in the world will eventually recognize this and
Speaker 6: build out their AI infrastructure.
Speaker 3: Jenson, you use the word resource, and that makes me
Speaker 3: think about the energy requirements here. I think on the
Speaker 3: cool you talk about how the next generation models will
Speaker 3: have many orders of magnitude greater compute needs. But how
Speaker 3: will the energy needs increase and what is the advantage
Speaker 3: you feel in Vidia has in that sense, Well.
Speaker 6: The most important thing that we do is increase the
Speaker 6: performance of and increase the performance and efficiency of our
Speaker 6: next generation. So Blackwell is many times more performance than
Speaker 6: Hopper at the same level of power used. And so
Speaker 6: that's energy efficiency, more performance with the same amount of
Speaker 6: power or same performance at a lower power And that's
Speaker 6: number one. And the second is using luca cooling. We
Speaker 6: support air cool we support air cooling, we support liqual cooling,
Speaker 6: but liqual cooling is a lot more energy efficient, and
Speaker 6: so the combination of all of that you're going to
Speaker 6: get a pretty large, pretty large step up. But the
Speaker 6: important thing to also realize is that AI doesn't really
Speaker 6: care where it goes to school, and so increasingly we're
Speaker 6: going to see AI be trained somewhere else, have that
Speaker 6: model come back and be used near the population, or
Speaker 6: even running on your PC or your phone. And so
Speaker 6: we're going to train large models. But the goal is
Speaker 6: not to run the large models necessarily all the time.
Speaker 6: You can, you can surely do that for some of
Speaker 6: the premium services and the very high value AIS, but
Speaker 6: it's very likely that these large models would then help
Speaker 6: to train and teach smaller models, and what we'll end
Speaker 6: up doing is have one large, few large models that
Speaker 6: are able to train a whole bunch of small models,
Speaker 6: and they run everywhere.
Speaker 3: Jensen, you explain clearly that demand to build generative AI
Speaker 3: product on models or even at the GPU level is
Speaker 3: greater than current supply. In black Wealth's case in particular,
Speaker 3: explain the supply dynamics to me for your products and
Speaker 3: whether you see an improvement sequentially quarter on quarter or
Speaker 3: at some point by the end of fiscal year into
Speaker 3: next year.
Speaker 6: Well, the fact that we're growing would suggest that our
Speaker 6: supply is improving and our supply chain is quite large.
Speaker 6: One of the largest supply chains in the world. We
Speaker 6: have incredible partners and they're doing a great job supporting
Speaker 6: us in our growth. As you know, we're one of
Speaker 6: the fastest growing technology companies in history. None of that
Speaker 6: would have been possible without very strong demand but also
Speaker 6: very strong supply. We're expecting Q three to have more
Speaker 6: supply than Q two, We're expecting Q four to have
Speaker 6: more supply than Q three, and we're expecting Q one
Speaker 6: to have more supply than Q four, And so I
Speaker 6: think our supply, our supply condition going into next year
Speaker 6: will be in will be a large improvement over this
Speaker 6: last year with respect to demand. Blackwell is just such
Speaker 6: a leap and there's several things that are happening, you know,
Speaker 6: just the Foundation model makers themselves. The size of the
Speaker 6: Foundation models are growing from hundreds of billions parameters to
Speaker 6: trillions of parameters. They're also learning more languages. Instead of
Speaker 6: just learning human language, they're learning the language of images
Speaker 6: and sounds and videos, and they're even learning the language
Speaker 6: of three D graphics. And whenever they are able to
Speaker 6: learn these languages, they can understand what they see, but
Speaker 6: they can also generate what they're asked to generate and
Speaker 6: so they're learning the language of routines and chemicals and physics.
Speaker 6: You know, it could be fluids and it could be
Speaker 6: particle physics, and so they're learning all kinds of different languages,
Speaker 6: learned the meaning of what we call modalities, but basically
Speaker 6: learning languages. And so these models are growing in size,
Speaker 6: they're learning from more data, and there are more model
Speaker 6: makers then there was a year ago. And so the
Speaker 6: number of model makers have grown substantially because of all
Speaker 6: these different modalities. And so that's just one, just the
Speaker 6: frontier model. The foundation model makers themselves haven't really grown tremendously.
Speaker 6: And then the generative AI market has really diversified, you know,
Speaker 6: beyond the Internet service makers to startups and now enterprises
Speaker 6: are jumping in and different countries are jumping in, so
Speaker 6: the demand is really growing.
Speaker 3: Jensen, I'm sorry to cut you off. I will lose
Speaker 3: your time soon. You've also diversified. And when I said
Speaker 3: to our audience you were coming on, I got so
Speaker 3: many questions. Probably the most common one is what is
Speaker 3: in Vidia. We talked about you as a systems vendor,
Speaker 3: but so many points on in Vidia Gpu Cloud, and
Speaker 3: I want to ask finally, do you have plans to
Speaker 3: become literally a cloud compute provider.
Speaker 6: No. Our GPU cloud was designed to be the best
Speaker 6: version of Nvidia Cloud that's built within each cloud. Nvidio
Speaker 6: DGX cloud is built inside GCP, inside Azure, inside AWS,
Speaker 6: inside OCI, and so we build our clouds within THEIRS
Speaker 6: so that we can implement our best version of our cloud,
Speaker 6: work with them to make that cloud, that that infrastructure,
Speaker 6: that AI infrastructure in Nvidia infrastructure, as performance, as great
Speaker 6: TCO as possible, and so that strategy has worked incredibly well.
Speaker 6: And of course we are large consumers of it because
Speaker 6: we create a lot of AI ourselves, because our chips
Speaker 6: aren't possible to design without AI, our software is not
Speaker 6: possible to write without AI, and so we use it
Speaker 6: ourselves tremendous, you know, tremendous amount of it self driving cars,
Speaker 6: the general robotics work that we're doing, the omniverse work
Speaker 6: that we're doing. So we're using the DGX cloud for ourselves.
Speaker 6: We also use it for an AI foundry. We make
Speaker 6: AI models for companies that would like to have expertise
Speaker 6: in doing so, and so we are AI. We're an AI,
Speaker 6: we're a foundry for AI. Like tsmcs a foundry for
Speaker 6: our chips and so so there are three fundamental reasons
Speaker 6: why we do it. One is to have the best
Speaker 6: version of Nvidia inside all the clouds. Two because we're
Speaker 6: a large consumer to ourselves, and third because we use
Speaker 6: it for AI foundry for to help every other company.
Speaker 3: Jensen one, CEO and video. I want to thank you
Speaker 3: for your time the extended conversation straight off the earnings
Speaker 3: called thank you in earnings fiscal it's good to see
Speaker 3: you too called second quarter. Then I point out that
Speaker 3: in after hours the stock is down still almost seven percent.
Speaker 3: There'll be a lot of analysis to be done overnight
Speaker 3: by the cell side, by the byside, and we'll bring
Speaker 3: you the best from Bloomberg's reporters and editors from San Francisco.
Speaker 3: This is Bloomberg Technology